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cosmicstack-labs avatar

cosmicstack-labs/mercury-agent

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Mercury Agent

Mercury Agent is a personal AI agent that runs as a long-lived background process on your own machine. It restarts after crashes and at login, keeps working on tasks after the terminal is closed, and serves every connected chat channel from one shared local memory. The same agent can be reached from a terminal, Telegram, Discord, Slack, Signal and a local web dashboard, with access rules such as pairing codes and admin roles applied per channel.

Every file edit, shell command, network fetch and git action is checked against folder scopes, a fixed blocklist and per-session approval modes before it runs. Language model requests go to a default provider first and fall back down a ranked list of hosted, local or OpenAI-compatible endpoints when one fails. A daily token budget is counted on every turn, and as usage approaches the cap the agent trims context or sends routine work to cheaper models. The agent's character and behavior are defined in plain Markdown files you can edit.

Beyond chat, it covers coding inside a repository, where it plans changes with a live checklist and reports success only after a build, test or typecheck passes. It can also create scheduled specialist bots with their own personas, models, memory, permissions and budgets. Work can be tracked on Kanban boards that run cards in dependency order, with per-card token tracking and recurring or one-time jobs that report back to the originating channel. Facts from conversations are stored in a local database and recalled before each answer. Community skills that follow the Agent Skills specification can be searched, reviewed and installed to extend what the agent can do.

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mercuryagent.sh
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Features

  • Personal AI Assistants - Provides a local-first personal AI assistant that survives crashes, keeps shared memory, and continues tasks after the terminal is closed.
  • Background Agent Runs - Runs the agent as a persistent background service that restarts after crashes and serves every connected channel from one shared memory.
  • Persistent Agent Hosting - Runs a long-lived agent on your own machine that restarts after crashes and at login and keeps serving all connected channels.
  • Provider Fallback Chains - Sends each model request to a default provider first and falls back down a ranked list of hosted, local or compatible endpoints.
  • Shared Cross-Channel Memory - Keeps one local database of extracted facts that all chat channels share, so context carries over between them.
  • Repository Coding Sessions - Opens a full-screen coding session that plans and builds repository changes and marks work complete only after a build or test passes.
  • Automation Permissions - Controls which file edits, shell commands, network fetches and git actions an assistant may run, using scoped rules and approval modes.
  • Assistant Messaging Channels - Connects an AI assistant to Telegram, Discord, Slack, Signal, a terminal and a web dashboard for two-way conversations with shared context.
  • Action Permission Gates - Checks every file edit, shell command, network fetch and git action against folder scopes, a fixed blocklist and per-session approval modes.
  • Agent Tool Permissions - Limits file, command, network and git access to approved folders through scoped rules, a fixed blocklist and per-session approval modes.
  • Background Service Daemonization - Runs as one long-lived background process that restarts after crashes and at login and keeps serving tasks after the terminal closes.
  • Chat Channel Integrations - Connects one agent to the terminal, Telegram, Discord, Slack, Signal and a local web dashboard with per-channel pairing codes and admin roles.
  • Agent Code Editing - Plans and edits code in a repository with a live checklist and reports success only after a build, test or typecheck passes.
  • Agent Orchestration Frameworks - Manages specialist bots with persistent memory, schedules tasks, tracks Kanban cards in dependency order and collects finished files.
  • Dynamic Model Switching - Connects to hosted, local and OpenAI-compatible models and switches to another model automatically when the current one is unavailable.
  • Bot-to-Bot Task Delegation - Creates scheduled specialist bots with their own personas, budgets and permissions, hands them tasks, tracks Kanban work and collects finished files.
  • Markdown-Defined Personas - Loads the agent's character, taste and behavior from plain Markdown files that users can read and edit freely.
  • Multi-Provider LLM Gateways - Routes requests over hosted, local and OpenAI-compatible models, falls back on failure, and keeps usage within a daily token budget.
  • Verified Repository Coding Agents - Plans repository changes with a live checklist and reports success only after a build, test or typecheck passes.
  • Agent Context and Memory - Extracts facts from conversations into typed local memory, recalls relevant ones before each answer, and merges or ages out stored memories hourly.
  • AI Token Budget Controllers - Enforces a daily token budget on every turn, shrinking context or using cheaper models as usage climbs and reporting what remains.
  • Kanban Boards - Tracks work on Kanban boards, running cards in dependency order with per-card token tracking and scheduled jobs reporting back to the origin channel.
  • Markdown Configurations - Defines the agent's character, persona and regular behavior through plain Markdown files that users can read and edit.
  • Verified Coding Task Automation - Plans and implements repository changes with a live checklist, asks before large edits, and reports success only after build, test or typecheck passes.
  • LLM Provider Failovers - Tries a default model provider first and falls back down a ranked list of hosted, local or OpenAI-compatible endpoints when one fails.
  • Pre-Action Permission Checks - Checks file access against per-folder scopes and screens shell commands and other actions before they run.
  • Dependency-Ordered Task Execution - Runs Kanban cards in dependency order and passes along results, with per-card token tracking and jobs that report back to their origin channel.
  • Long-Lived Bot Processes - Keeps long-lived specialist bots running with their own persona, model, memory and budget, working on schedules and handing tasks to each other.
  • Agent Skill Packages - Loads community skill packages that follow a shared specification into the agent at runtime to extend its abilities.
3,883 stars·398 forks·TypeScript·MIT·0 views

Star history

Star history chart for cosmicstack-labs/mercury-agentStar history chart for cosmicstack-labs/mercury-agent

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Projects sharing features with Mercury Agent

These projects share indexed features with Mercury Agent. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • open-jarvis/openjarvisopen-jarvis avatar

    open-jarvis/OpenJarvis

    13,786View on GitHub↗

    OpenJarvis is a local-first personal AI assistant and agent framework. It runs language models on a user's own laptop, workstation, or server, keeps agent memory and state on the device, and treats cloud services as optional extras. Agents reason over multiple steps, call tools, search documents, and can run on demand, on a cron schedule, or continuously in the background. Core functionality stays available offline. A unified inference layer connects local runtimes and optional cloud providers behind one interface. It detects the installed GPU vendor, model, and memory, then recommends a suit

    Python
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  • tashfeenahmed/freellmapitashfeenahmed avatar

    tashfeenahmed/freellmapi

    48,827View on GitHub↗

    freellmapi is a self-hosted gateway that combines the free tiers of many language model providers behind one local, OpenAI-compatible endpoint. Applications talk to a single address with a single bearer token, while the router chooses a provider and model for each request and retries on another when one errors or hits its limit. Provider keys are stored encrypted in a local database, and per-key rate limits are tracked against per-minute and per-day ceilings. Beyond the OpenAI-style format for chat, completion, embedding, image, video, and speech requests, the router also accepts Anthropic, G

    TypeScript
    View on GitHub↗48,827
  • linuxhsj/openclaw-zero-tokenlinuxhsj avatar

    linuxhsj/openclaw-zero-token

    5,213View on GitHub↗

    OpenClaw Zero Token is a self-hosted gateway and assistant platform that lets people chat with browser-based AI services such as ChatGPT, Claude, Gemini, DeepSeek, Kimi and Grok without paying for API tokens. It captures a login from a debuggable Chrome browser through the Chrome DevTools Protocol, then reuses that session's cookies and headers for later requests. A single OpenAI-compatible chat completions endpoint, secured by a bearer token, routes each request to whichever web model is configured, so outside programs can call those models like a standard API. Because web chat models have n

    TypeScript
    View on GitHub↗5,213
  • lintsinghua/claude-code-booklintsinghua avatar

    lintsinghua/claude-code-book

    4,359View on GitHub↗

    This repository is a long-form technical book about how a production AI coding agent runtime, often called an agent harness, is built. It dissects a real-world coding agent's architecture chapter by chapter and turns it into transferable lessons, and it also works as a step-by-step guide to designing and building your own harness around a language model. Python scripts in the repository support the book itself rather than the agent. The book's core subject is the machinery around the model: a streaming conversation loop that repeats tool calls until the model returns plain text, a tool protoc

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Compare all 30 related projects→

Frequently asked questions

What does cosmicstack-labs/mercury-agent do?

Mercury Agent is a personal AI agent that runs as a long-lived background process on your own machine. It restarts after crashes and at login, keeps working on tasks after the terminal is closed, and serves every connected chat channel from one shared local memory. The same agent can be reached from a terminal, Telegram, Discord, Slack, Signal and a local web dashboard, with access rules such as pairing codes and admin roles applied per channel.

What are the main features of cosmicstack-labs/mercury-agent?

The main features of cosmicstack-labs/mercury-agent are: Personal AI Assistants, Background Agent Runs, Persistent Agent Hosting, Provider Fallback Chains, Shared Cross-Channel Memory, Repository Coding Sessions, Automation Permissions, Assistant Messaging Channels.

Which projects share features with cosmicstack-labs/mercury-agent?

Projects with overlapping indexed features include: open-jarvis/openjarvis — OpenJarvis is a local-first personal AI assistant and agent framework. It runs language models on a user's own laptop,… tashfeenahmed/freellmapi — freellmapi is a self-hosted gateway that combines the free tiers of many language model providers behind one local,… linuxhsj/openclaw-zero-token — OpenClaw Zero Token is a self-hosted gateway and assistant platform that lets people chat with browser-based AI… lintsinghua/claude-code-book — This repository is a long-form technical book about how a production AI coding agent runtime, often called an agent… elie222/rakazo — Rakazo is a self-hosted, open-source platform of persistent AI bots. Each bot keeps its own conversations, memory,… ebony-vinyl/dsh-our-free-model — This is a plugin for the dsh tool that adds a local gateway to many hosted language models. The gateway accepts…